List of currencies and their 3 digit codes as defined by ISO 4217. The data provided here is the consolidation of Table A.1 "Current currency & funds code list" and Table A.3 "Historic denominations".Note that the ISO page offers pay-for PDFs but also links to http://www.currency-iso.org/en/home/tables.html which does provide them in machine readable form freely.

The Currencies data collected from the Mental Health Services Data Set.The Mental Health Services Data Set (MHSDS) collects data from the health records of individual children, young people and adults who are in contact with mental health services. The data is re-used for purposes other than their direct care and as such is referred to as a secondary uses data set. It defines data items, definitions and information extracted or derived from local information systems.

Analysis of ‘International investment position - quarterly data, million units of national currency’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://data.europa.eu/data/datasets/jfwepte0h3esvyixzh5hza on 30 September 2021.

--- Dataset description provided by original source is as follows ---

The international investment position (IIP) is a statistical statement that shows at a point in time the value and composition of: -financial assets of residents of an economy that are claims on non-residents and gold bullion held as reserve assets, and -liabilities of residents of an economy to non-residents. The difference between an economy’s external financial assets and liabilities is the economy’s net IIP, which may be positive or negative. The indicator is based on the Eurostat data from the Balance of payment statistics, i.e. the same data source used for the current account balance. The data are expressed in million units of national currency. Definitions are based on the IMF Sixth Balance of Payments Manual (BPM6).

--- Original source retains full ownership of the source dataset ---

The international investment position (IIP) is a statistical statement that shows at a point in time the value and composition of: -financial assets of residents of an economy that are claims on non-residents and gold bullion held as reserve assets, and -liabilities of residents of an economy to non-residents. The difference between an economy’s external financial assets and liabilities is the economy’s net IIP, which may be positive or negative. The indicator is based on the Eurostat data from the Balance of payment statistics, i.e. the same data source used for the current account balance. The data are expressed in million units of national currency. Definitions are based on the IMF Sixth Balance of Payments Manual (BPM6).

This dataset is about book series. It has 1 row and is filtered where the books is Linkages between excess currency and stock market returns : Granger causality in mean and variance. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

​Significant changes to the open data catalogue, including new datasets added, datasets renamed or retired, quarterly or annual updates to high-impact datasets, changes to data structure or definition. Smaller changes, such as adding or editing records or renaming a field in an existing dataset are not included. NoteThis log is published in the interest of transparency into the work of the open data program. You can subscribe to updates for a specific dataset by creating an account on the portal then clicking on the Follow button on the Information tab of any dataset. You can get updates by subscribing to our email newsletter. Data currency​New records will be added whenever a significant change is made to the open data catalogue.

This table contains information on general government debt. Debt is broken down into debt instruments and counterpart sectors (debt holders). Government debt is presented at face value (redemption value of debt) as well as market value (value at which debt can be traded). General government debt according to the Maastricht-definitions relevant in the Stability and Growth Pact is valued at face value, whereas the market value is applied in national accounts. Government debt denominated in euros as well as debt denominated in foreign currency are separately disclosed. Foreign currency debt is valued at prevailing currency exchange rate. The figures are consolidated which means that flows between units that belong to the same sector of general government are eliminated. As a result, the debt of subsectors do not add up to total debt of general government. For example, debt of the State to social security funds is part of debt of the State. However, it is not included in the consolidated debt of general government, because it is debt of general government to general government. The terms and definitions used are in accordance with the framework of the national accounts. National accounts are based on the international definitions of the European System of Accounts (ESA 2010). Small temporary differences in this table with publications of the Dutch national accounts may occur due to the fact that the Dutch government finance statistics are sometimes more up to date.

Data available from: Yearly figures from 1995, quarterly figures from 1999.

Status of the figures: The figures for the period 1995-2023 are final. The figures for 2024 and 2025 are provisional.

Changes as of 24 June 2025: The figures for the first quarter of 2025 are available. Figures for 2023 and 2024 have been adjusted due to updated information. The figures for 2023 are final. In the context of the revision policy of National accounts, the annual figures from 1995 and the quarterly figures from 1999 have been revised.

When will new figures be published? Provisional quarterly figures are published three months after the end of the quarter. In September the figures on the first quarter may be revised, in December the figures on the second quarter may be revised and in March the first three quarters may be revised. Yearly figures are published for the first time three months after the end of the year concerned. Yearly figures are revised two times: 6 and 18 months after the end of the year. Please note that there is a possibility that adjustments might take place at the end of March or September, in order to provide the European Commission with the latest figures. Revised yearly figures are published in June each year. Quarterly figures are aligned to revised years at the end of June. More information on the revision policy of Dutch national accounts and government finance statistics can be found under 'relevant articles' under paragraph 3.

Analysis of ‘Private sector credit flow: loans by sectors, non-consolidated - million units of national currency’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://data.europa.eu/data/datasets/5a5msphjfegxkne25clrg on 29 August 2021.

--- Dataset description provided by original source is as follows ---

The table presents the net flow of loans (F.4) for the sectors Non-Financial corporations (S.11), Households (S.14) and Non-Profit institutions serving households (S.15). The debt securities are negotiable financial instruments serving as evidence of debt. Data are presented in non-consolidated terms, i.e. data take into account transactions within the same sector and expressed in Million units of national currency. Definitions regarding sectors and instruments are based on the ESA 2010.

--- Original source retains full ownership of the source dataset ---

The Foreign Currency Positions Weekly Report of Major Market Participants contains foreign currency holdings of large foreign exchange market participants. This table presents the currency data reported weekly by major market participants. This table provides information on positions in derivative instruments, such as foreign exchange futures and options that are increasingly used in establishing foreign exchange positions. Weekly reports must be filed throughout the calendar year by major foreign exchange market participants, which are defined as market participants with more than $50 billion equivalent in foreign exchange contracts on the last business day of any calendar quarter during the previous year (end March, September, September, or December). Such contracts include the amounts of foreign exchange spotcontracts bought and sold, foreign exchange forward contracts bought and sold, foreign exchange futures bought and sold, and one half the notional amount of foreign exchange options bought and sold. The information in the table is based on the reports referenced in this Introduction: Foreign Currency Positions and is not audited by the Federal Reserve banks or the Treasury Department. Please note that these amounts are reported in the foreign currency specified.

The Nobel Prize is a set of annual international awards bestowed in several categories by Swedish and Norwegian institutions in recognition of academic, cultural, or scientific advances. The will of the Swedish chemist, engineer and industrialist Alfred Nobel established the five Nobel prizes in 1895. The prizes in Chemistry, Literature, Peace, Physics, and Physiology or Medicine were first awarded in 1901. The prizes are widely regarded as the most prestigious awards available in their respective fields The dataset titled "complete.csv" contains detailed information on Nobel Prize laureates and their awards, spanning various years and categories. Here's a comprehensive metadata description of this dataset: General Overview: Total Entries: 950 Total Columns: 52 Time Frame: The dataset includes Nobel Prize data from the year 1901 to 2019. Column Details: Primary Identifiers: awardYear, category, id, name. Personal Details: knownName, givenName, familyName, fullName, penName, gender. Birth and Death Information: birth_date, birth_city, birth_country, death_date, death_city, death_country, etc. Nobel Prize Details: categoryFullName, sortOrder, portion, prizeAmount, prizeAmountAdjusted, dateAwarded, prizeStatus, motivation. Affiliation and Location: Various fields for affiliation and location details, like birth_continent, birth_countryNow, residence_1, affiliation_1, affiliation_2, etc. Additional Information: categoryTopMotivation, award_link, laureate_link, and more. Data Types: The dataset contains a mix of integers (int64), strings (object), and a few date fields. Data Completeness: Certain fields, like dateAwarded, penName, death_date, have a significant number of missing values. The core details like awardYear, category, prizeAmount, and laureate names are mostly complete. Statistical Overview: awardYear: Ranges from 1901 to 2019. sortOrder: Indicates the order of the award, ranging from 1 to 3. prizeAmount: Ranges widely, with a mean of approximately 3.46 million (currency not specified). prizeAmountAdjusted: Also varies, with a mean of approximately 6.15 million (currency not specified). Usage: This dataset is ideal for historical analysis of Nobel Prizes, understanding trends over time, and studying individual laureates' details. Access: The dataset is provided as a CSV file, suitable for analysis in various data processing software.

Government debt (in millions EUR) is defined as the total consolidated gross debt at nominal value in the

following categories of government liabilities (as defined in ESA 2010): currency and deposits Dimension Categories ( (AF.2), debt securities (AF.3) and loans (AF.4)

Tribal Census TractsThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau (USCB), depicts American Indian tribal census tracts. Per the USCB, "a tribal census tract is a relatively permanent statistical subdivision of a federally recognized American Indian reservation and/or off-reservation trust land, delineated by the American Indian tribal government and/or the Census Bureau for the purpose of presenting demographic data. For federally recognized American Indian Tribes with reservations and/or off-reservation trust lands with a population less than 2,400, a single tribal census tract is defined. Qualifying areas with a population greater than 2,400 could define additional tribal census tracts within their area". Data currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Tribal Census Tracts) and will support mapping, analysis, data exports and OGC API – Feature access.Data.gov: TIGER/Line Shapefile, 2019, nation, U.S., Current Tribal Census Tract NationalGeoplatform: TIGER/Line Shapefile, 2019, nation, U.S., Current Tribal Census Tract NationalFor more information, please visit: Decoding State-County Census Tracts versus Tribal Census TractsFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the "boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes."For other NGDA Content: Esri Federal Datasets

The Foreign Currency Positions Monthly Report of Major Market Participants contains foreign currency holdings of large foreign exchange market participants. This table presents more detailed currency data of major market participants, based on monthly reports. This table provides information on positions in derivative instruments, such as foreign exchange futures and options that are increasingly used in establishing foreign exchange positions. Monthly reports must be filed throughout the calendar year by major foreign exchange market participants, which are defined as market participants with more than $50 billion equivalent in foreign exchange contracts on the last business day of any calendar quarter during the previous year (end March, September, September, or December). Such contracts include the amounts of foreign exchange spotcontracts bought and sold, foreign exchange forward contracts bought and sold, foreign exchange futures bought and sold, and one half the notional amount of foreign exchange options bought and sold. The information in the table is based on the reports referenced in this Introduction: Foreign Currency Positions and is not audited by the Federal Reserve banks or the Treasury Department. Please note that these amounts are reported in the foreign currency specified.

Dataset replaced by: http://data.europa.eu/euodp/data/dataset/HwYivJu1Okf3aePpVpGGtw The indicator is defined (in the Maastricht Treaty) as consolidated general government gross debt at nominal (face) value, outstanding at the end of the year in the following categories of government liabilities (as defined in ESA 2010): currency and deposits, debt securities and loans. The general government sector comprises the subsectors: central government, state government, local government and social security funds.

The data set includes >18,000 Irish organisations that fall within an internationally-recognised definition of civil society. They are voluntary, constituted on a not-for-profit basis, independent of government, autonomous in their governance and established to some meaningful degree.

Benefacts, which itself is a civil society organisation - has identified the data set using internationally-recognised classification norms. It has derived the data set from more than ten distinct regulatory sources, drawing on open data files and other documents published by Irish regulators and other government authorities.

Besides the name and address of each nonprofit, the data set includes - the names of the regulators with which each nonprofit is registered and their respective registration numbers; - a sub-sectoral classification assigned to each nonprofit by Benefacts (using a localised version of internationally-recognised classification standards) - a link to the listing for each entity published by Benefacts on its public website benefacts.ie

Benefacts relies on public sources of data - not all of it available in open formats - to build its database. Sometimes data is derived from more than one source, and the currency of information can vary. Using the best data available at the time, Benefacts updates its database - and hence this data set - at least daily.

The table presents the stock of liabilities of debt securities (F.3) for the sectors Non-Financial corporations (S.11), Households (S.14) and Non-Profit institutions serving households (S.15). The debt securities are negotiable financial instruments serving as evidence of debt. Data are presented in consolidated terms, i.e. data do not take into account transactions within the same sector and expressed in million units of national currency. Definitions regarding sectors and instruments are based on the ESA 2010.

Waterway Network NodesThis National Geospatial Data Asset (NGDA) dataset, shared as a United States Army Corps of Engineers (USACE) feature layer, displays navigable waterway nodes. Per USACE, The National Waterway Network (NWN) “is comprised of a link database and a node database. Nodes may represent physical entities such as river confluence's, ports/facilities, and intermodal terminals, USACE nodes, or may be inserted for analytical purposes (i.e., to facilitate routing).”Waterway Node 34580 (Washington, D.C.)Data currency: current federal service (Waterway Network Node)NGDAID: 154 (Navigable Waterway Nodes (National) - National Geospatial Data Asset (NGDA) Waterway Nodes)For more information, please visit: Definition of Navigable Waters of the USFor feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Transportation Theme Community. Per the Federal Geospatial Data Committee (FGDC), Transportation is defined as the "means and aids for conveying persons and/or goods. The transportation system includes both physical and non-physical components related to all modes of travel that allow the movement of goods and people between locations".For other NGDA Content: Esri Federal Datasets